ArticleFrontiers in cardiovascular medicine2024
Enhanced fibrotic potential of COL1A1
Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- CMKLR1 as a Therapeutic Target: Vitamin D-Mediated Suppression of Inflammation and Oxidative Stress in SA-AKI.Molecular biotechnology · 2026Article
- EZH2 inhibition via GSK-126 mitigates EndMT and atherosclerosis in diabetes: A translational epigenetic approach.Science advances · 2026Article
- Cardiac fibroblasts in myocardial injury and heart failure.European heart journal · 2026Review
- Cardiac fibroblast heterogeneity in cardiac fibrosis implication for cell-type-specific treatment.Frontiers in physiology · 2026Review
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Fibroblasts in the fibrotic heart exhibit a heterogeneous biological behavior. The specific subsets of fibroblasts that contribute to progressive cardiac fibrosis remain unrevealed. Our aim is to identify the heart fibroblast (FB) subsets that most significantly promote fibrosis and the related critical genes as biomarkers for ischemic heart disease. Methods: The single nuclei RNA sequencing (snRNA-seq) and bulk RNA sequencing datasets used in this study were obtained from the Gene Expression Omnibus (GEO). The activity of gene sets related to progressive fibrosis was quantified for each FB cluster using the AddmoleculeScore function. Differentially expressed genes (DEGs) for the specific cell cluster with the highest fibrotic transcription dynamics were identified and integrated with bulk RNA sequencing data for analysis. Multiple machine learning models were employed to identify the optimal gene panel for diagnosing ischemic heart disease (IHD) based on the intersected DEGs. The effectiveness and robustness of the gene-derived diagnostic tool were validated using two independent IHD cohorts.Subsequently, we validated the signature genes using a rat post-myocardial infarction heart failure model. Results: We conducted an analysis on high-quality snRNA-seq data obtained from 3 IHD and 4 cardiac sarcoidosis heart samples, resulting in the identification of 16 FB clusters. Cluster2 exhibited the highest gene activity in terms of fibrosis-related transcriptome dynamics. The characteristic gene expression profile of this FB subset indicated a specific upregulation of COL1A1 and several pro-fibrotic factors, including CCDC102B, GUCY1A3, TEX41, NREP, TCAP, and WISP, while showing a downregulation of NR4A1, an endogenous inhibitor of the TGF- Conclusion: COL1A1
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